ABOUT THE ROLEBaselayer is building the most comprehensive, accurate, and continuously-current identity graph of US businesses - fusing public records, IRS data, sanctions lists, web signals, and fraud telemetry from thousands of financial institutions into a single graph that resolves any business in milliseconds. None of that works without world-class data infrastructure. We're hiring a Data Engineer to help build and run the pipelines and models that turn messy, heterogeneous data into trustworthy, production-grade signal. You'll write real production code in your first weeks, own pipelines end to end, and learn alongside senior data and ML engineers who will invest in your growth. This is a role for an early-career engineer who wants to be close to the action: feeding the models, not just cleaning up after them.
WHAT YOU'LL DO- Build and maintain ETL/ELT pipelines that ingest and normalize public records, web signals, and fraud telemetry from dozens of sources
- Develop data models and transformation layers (Dataflow, Spark, Airflow) that power fraud detection, KYB, and customer-facing APIs
- Implement data quality checks, observability tooling, and alerting so problems surface before customers see them
- Tune pipelines and queries for performance, freshness, and cost in our cloud data warehouse
- Work with data scientists, ML engineers, and product to make clean, well-modeled data available for entity resolution and scoring
- Help ensure pipelines meet security and regulatory standards for sensitive data (SOC 2, GDPR, KYC/KYB)
- Document what you build and translate between technical and non-technical stakeholders so the rest of the team moves faster
MINIMUM REQUIREMENTS- 1+ years of experience in data engineering, working with Python, SQL, and cloud-native data platforms
- Experience building and maintaining ETL/ELT pipelines in a production environment
- Working knowledge of modern data stack tooling (e.g. Dataflow, Spark, Airflow or equivalents)
- Hands-on experience with cloud data warehouses or lakes (e.g. BigQuery, Snowflake, or equivalents)
- Solid data modeling fundamentals and real care for data integrity and reliability
- Comfort with both structured and unstructured data, and a feel for what clean, scalable architecture looks like
WHAT SETS YOU APART- Curiosity about AI/ML infrastructure and a desire to be close to the models, not just the cleanup after them
- Experience with streaming or real-time data systems (e.g. Kafka, Pub/Sub)
- Exposure to KYC/KYB, fraud, risk, or underwriting data, and the ethical care that sensitive information demands
- GCP experience (BigQuery, Cloud Run, Dataflow, Pub/Sub)
- You care deeply about data quality and trust, and build systems others can rely on
- You've worked without a playbook before, and you take direct feedback well and act on it fast
WORK LOCATION- Based in SF; hybrid - 4 days per week in office.
COMPENSATION- Salary Range: $120,000 - $150,000 + Equity
BENEFITS- Time off when you need it: Flexible PTO so you can recharge without red tape.
- In-person energy: We're based in SF and meet in the office 4 days a week.
- Competitive compensation: We pay well and back it with equity. We want you to think and act like an owner.
- Career rocket fuel: You'll help build the foundation of a high-growth startup, working side by side with experienced founders and team members who've done it before.
- Benefits on us: We cover 100% of your health, dental, and vision premiums. No surprise deductions from your paycheck.
- 401(k) with company match: We match your contributions so your future self benefits too
- HSA contributions included: We contribute to your HSA on applicable plans, so your coverage works as hard as you do
- Stay healthy, stay sharp: A $250 monthly gym stipend to help you bring your best self to work, and everywhere else
- A seat at the table: We believe in transparency, radical candor, and giving every team member a voice
